Single Cell Analysis of Plasmacytoid dendritic cells to understand their heterogeneity for INterferon production – SCAPIN

We will use a systems biology strategy to identify the mechanisms controlling the production of IFN by pDC, including by testing whether and how it is partly determined by their heterogeneity at ground state. Specifically, we will characterize the gene expression program of resting or activated pDC, on well-identified subpopulations and by single-cell RNA-seq. From the analysis of these data, we will derive new hypotheses which will then be tested by combining targeted proteomic analyzes using mass cytometry and mutant mouse lines. Innovative bioinformatics methods will be used to analyze all the Omics data obtained and to generate a mathematical model of the signaling pathways in the pDC. This model will be screened experimentally to validate new therapeutic targets.

The analysis of the single cell RNA-seq data has revealed gene modules with exclusive expression patterns that could characterize successive phases of pDC activation. In order to achieve a high enrichment of the IFN-producing pDCs at the various stages of their activation, we have defined a strategy based on the combined use of EYFP and of new surface markers identified by sc-RNAseq and validated by FACS.

Combined with a kinetic analysis, our new strategy for enriching the pDC activated for IFN production will allow us to obtain sufficient sc-RNAseq data on the different putative activation stages pre-identified, in order to allow a more robust pseudo-time analysis. This will make it possible to reconstruct the activation trajectory of the IFN-producing pDC in order to determine the succession of the signals which they have received and the pathways which they have activated, in particular discriminating when and how the divergence of activation between the pDC that will produce IFN and those that will not.

None yet.

Our ability to fight infection and cancer relies on the coordination of the responses of our innate and adaptive immune cells, which is in a large part orchestrated by cytokines. Different types of immune cells exert distinct functions. Functional heterogeneity also exists within each immune cell type. A remarkable example of this intra-type heterogeneity is the restriction of cytokine production to a minor fraction of activated cells while other responses appear to be more broadly distributed.

The mechanisms regulating functional heterogeneity within a given type of immune cells largely remain to be identified, including with regards to cytokine production. Recent technological innovations enable the characterization of the gene expression programs of single primary cells. This approach revealed that a striking heterogeneity already exists at ground state in the gene expression programs of unstimulated individual cells within one given cell type. The biological meaning of this heterogeneity remains puzzling. One hypothesis is that ground state intra-type heterogeneity might participate to the induction of different responses in a population of cells of a given type upon exposure to a given stimulus. We propose to test this hypothesis by determining whether, and how, ground state heterogeneity within a given type of immune cells is related to functional heterogeneity upon activation.

We will focus our study on plasmacytoid dendritic cells (pDC) because they are a particularly striking example of the biological process we want to study and because a better understanding of the mechanisms regulating their cytokine production has important applications for human health. Activated pDC copiously produce type I interferon (IFN-I). Inhibition of this function increases susceptibility to viruses or cancers. Inappropriate activation of pDC IFN-I production causes auto-immune/inflammatory diseases. Only ~10% of activated pDC produce IFN-I.

We propose a systems biology strategy to identify novel molecular mechanisms controlling pDC IFN-I production. We will characterize the gene expression program of ground state (unstimulated) or activated pDC by performing microarray experiments on discrete pDC subsets and RNA-seq experiments on single cells. The analyses of these data will yield novel hypotheses on the stimuli and signaling pathways controlling pDC IFN-I production. The most interesting markers and signaling pathways will be further examined on single cells through a focused proteomic profiling, using mass cytometry to simultaneously measure the expression and post-translational modifications of about twenty candidate proteins. Innovative bioinformatics methodologies will be used to analyze all the Omics data obtained and to generate a mathematical model of signaling pathways in pDC. Model predictions will be confronted to functional measurement of the impact of experimental perturbations of pDC signaling pathways, which should allow identifying the most promising novel therapeutic targets.